Customized Sleep Training System and Method for Infants and Toddlers

Abstract

The present invention includes a sleep state detection unit that detects the sleep state of an infant in real time, including heart rate, body temperature, and movement. The detected data is analyzed by a data processing unit to identify sleep patterns, and continuously improved customized learning content is provided through an artificial intelligence learning module. The customized learning content provider offers various sleep content, such as white noise, fairy tales, and lullabies, and allows parents to monitor the sleep state and adjust settings in real time through a parent interface. This enables the formation of healthy sleep habits in infants and reduces the burden of childcare for parents.

Description

Technology Field

[0001] The present invention relates to a system and method for monitoring and analyzing the sleep state of infants and toddlers in real time to provide customized sleep learning programs and content. More specifically, the present invention relates to a smart system that supports improving the sleep patterns of infants and toddlers and forming healthy sleep habits based on a parent interface and an AI learning module. Background Technology

[0002] The matters described in this background technology section are written to enhance understanding of the background of the invention and may include matters that are not prior art already known to those skilled in the art to which this technology belongs.

[0003] Infancy and early childhood are critical periods for physical and brain development, making quality sleep essential. However, many parents experience a burden of childcare due to their infants' irregular sleep patterns and frequent awakenings. Existing sleep education methods often rely on standardized content and passive management, making it difficult to provide solutions tailored to individual characteristics and patterns. In particular, if sleep problems persist due to the lack of sleep education programs, it can have a negative impact on emotional stability and development. Furthermore, existing sleep learning systems cause inconvenience to both parents and infants because they are unable to analyze data in real time or offer limited customized content. Accordingly, there is an increasing need for a smart system that detects an infant's sleep status in real time, provides customized sleep content based on data, and allows parents to easily manage sleep patterns. This invention was created to solve these problems. The problem to be solved

[0004] The purpose of this invention is to provide customized sleep learning content based on data analysis by monitoring the sleep status of infants and toddlers in real time. Through this, the invention aims to support infants and toddlers in naturally forming healthy sleep habits and to provide parents with real-time monitoring and management tools that can reduce the burden of childcare. Furthermore, it seeks to achieve the effect of resolving sleep problems by providing continuously improved content through AI-based learning modules. means of solving the problem

[0005] A sleep learning system for infants and toddlers that detects the sleep state of an infant and toddler and provides customized learning content according to the present invention may include a sleep state detection unit comprising a heart rate sensor, a body temperature sensor, and a motion sensor for detecting the sleep state of an infant and toddler; a data processing unit comprising a sleep pattern analysis module and a learning content optimization module that collect and analyze data detected by the sleep state detection unit to derive a sleep pattern; a customized learning content provision unit comprising a customized white noise provision module, a story provision module, and a lullaby provision module that provides learning content according to the analysis results of the data processing unit; and a parent interface that allows parents to check the sleep state of the infant and toddler in real time and adjust settings through a state monitoring module and a setting adjustment module.

[0006] A customized sleep learning system for infants and toddlers according to the present invention, which supports improving sleep patterns by detecting the sleep state of an infant and toddler in real time and providing customized learning content, may include a sleep state detection unit that continuously monitors the sleep state based on the detected data, a sleep pattern analysis module that derives the sleep state and sleep pattern by analyzing data collected from the sleep state detection unit, a learning content optimization module that selects and provides learning content optimized for the sleep state of the infant and toddler based on the sleep pattern analysis results, a white noise providing module that provides white noise according to the sleep state derived from the data processing unit, a story providing module that provides story content for sleep induction and emotional stability, and a lullaby providing module that provides a lullaby to promote sleep, and a parent interface that supports parents in checking the sleep state and sleep pattern analysis data of the infant and toddler in real time through a state monitoring module and adjusting the playback settings, volume control, and playback time settings of the sleep learning content through a setting adjustment module.

[0007] In the above, the data processing unit collects data from the sleep state detection unit on an hourly, weekly, and monthly basis, and comprehensively analyzes sleep time, wakefulness frequency, and movement patterns during sleep to provide the sleep state of the infant as a quantified indicator.

[0008] In the above, the customized learning content provider can automatically adjust the playback time, volume, and repetition count of the content according to the sleep state of the infant, and can optimize the content delivery method by collecting response data of the infant.

[0009] As described above, the parent interface visualizes and provides the infant's sleep diary and sleep state analysis data in a graphical form, thereby enabling parents to grasp changes in the infant's sleep patterns at a glance.

[0010] In the above, the artificial intelligence learning module may include a data analysis learning module that continuously learns data collected from the sleep state detection unit and the data processing unit to analyze changes and improvements in sleep patterns and, accordingly, optimizes the method of providing customized learning content, and a content improvement module that improves sleep content.

[0011] A sleep learning method for infants and toddlers that improves sleep patterns by detecting and analyzing the sleep state of an infant and toddler and providing customized learning content according to the present invention comprises: a sleep state detection step in which, to detect the sleep state of an infant and toddler, heart rate data of the infant and toddler is detected through a heart rate sensor, body temperature data is detected through a body temperature sensor, and movement and posture changes during sleep are detected through a motion sensor, and data detected by a sleep state detection unit is collected in real time; a data processing and analysis step in which the data collected in the sleep state detection step is transmitted to a data processing unit, and the sleep state of the infant and toddler is quantified by analyzing data including hourly sleep duration, wakefulness frequency, body temperature fluctuations, and movement patterns through a sleep pattern analysis module, and customized learning content is derived according to the analyzed sleep state and sleep pattern using a learning content optimization module; and according to the results derived in the data processing and analysis step, white noise to induce sleep in the infant and toddler is provided through a white noise providing module, story content for the emotional stability of the infant and toddler is provided through a story providing module, and lullaby content to promote sleep is provided through a lullaby providing module, wherein the infant and toddler's reaction and sleep state A customized learning content provision step that automatically adjusts the volume, playback time, and repetition count of the content to provide the content; a monitoring and setting adjustment step through the parent interface that provides the sleep learning content and the sleep state data of the infant provided in the content provision step in a real-time visualized form through the status monitoring module of the parent interface, and allows parents to adjust settings such as the content playback time, volume, and type as needed through the setting adjustment module; and a step that continuously learns the data obtained from the sleep state detection step and the data processing and analysis step using the data analysis learning module of the artificial intelligence learning module.Based on the learned results, it may include a learning content improvement step through feedback that automatically improves and provides customized content optimized for the future sleep state and patterns of infants and toddlers via a content improvement module.

[0012] In the above, the artificial intelligence learning module comprehensively analyzes the sleep duration, wakefulness frequency, body temperature changes, and movement patterns of infants and toddlers based on data collected from the sleep state detection unit and the data processing unit, and learns the analyzed results through the data analysis learning module to automatically recommend learning content optimized according to changes in the sleep habits of infants and toddlers, and evaluates and improves the effectiveness of the provided learning content through the content improvement module. Effects of the invention

[0013] According to the present invention, it is possible to provide various content, such as white noise and fairy tales, tailored to the sleep state of infants and toddlers.

[0014] In addition, parents can check and manage the sleep status of infants and toddlers in real time through a parent application.

[0015] In addition, it can continuously learn from data based on AI to provide customized solutions and improve sleep patterns.

[0016] Overall, the present invention reduces the burden of childcare for parents, enables efficient sleep education, and supports emotional stability and healthy growth for infants and toddlers.

[0017] The effects according to the present invention are not limited to those presented above, and various other effects are included in this specification. Brief explanation of the drawing

[0018] The embodiments of this specification may be better understood by referring to the following description in conjunction with the attached drawings, in which similar reference numerals refer to identical or functionally similar elements. Figure 1 is a conceptual diagram of customized sleep learning for infants and toddlers according to the present invention. Figure 2 is a block diagram of a customized sleep learning system for infants and toddlers according to the present invention. Figure 3 illustrates a block diagram of the customized sleep learning system for infants and toddlers according to the present invention. Figure 4 is a diagram illustrating the function of the sleep state detection unit. Figure 5 is a diagram illustrating the functions of the customized learning content provision unit. Figure 6 is a diagram illustrating the parent interface function. FIG. 7 is a drawing illustrating an example of sleep education according to the present invention. FIG. 8 is a flowchart illustrating a customized sleep learning method for infants and toddlers according to the present invention. FIG. 9 is a diagram illustrating the additional implementation of artificial intelligence functions in a customized sleep learning method for infants and toddlers according to the present invention. FIG. 10 is a drawing illustrating an application in which the present invention is implemented. The drawings referenced above are not necessarily drawn to scale and should be understood as presenting somewhat simplified representations of various preferred features illustrating the basic principles of the present disclosure. For example, specific design features of the present disclosure, including specific dimensions, orientations, positions, and shapes, will be partially determined by specific intended applications and usage environments. Specific details for implementing the invention

[0019] Hereinafter, some embodiments of the present disclosure will be described in detail with reference to the exemplary drawings. In assigning reference numerals to the components of each drawing, the same components may have the same reference numeral as much as possible, even if they are shown in different drawings. Furthermore, in describing the embodiments, if it is determined that a detailed description of related known components or functions may obscure the essence of the technical concept, such detailed description may be omitted. Where terms such as "comprising," "having," or "consisting of" are used in this specification, other parts may be added unless "only" is used. Where a component is expressed in the singular, it may include a plural unless otherwise specified. Additionally, in describing the components of the present disclosure, terms such as first, second, A, B, (a), (b), etc., may be used. These terms are used merely to distinguish the component from other components, and the essence, order, sequence, or number of the component is not limited by such terms.

[0020] In describing the positional relationship of components, where it is stated that two or more components are "connected," "combined," or "connected," it should be understood that while the two or more components may be directly "connected," "combined," or "connected," they may also be "connected," "combined," or "connected" with other components "intervened." Here, other components may be included in one or more of the two or more components that are "connected," "combined," or "connected" to each other. In describing the temporal flow relationship regarding components, methods of operation, or methods of production, where a temporal or sequential relationship is described using, for example, "after," "following," "next," or "before," cases that are not continuous may be included unless "immediately" or "directly" is used.

[0021] FIG. 1 is a conceptual diagram of a customized sleep learning system for infants and toddlers according to the present invention, FIG. 2 is a block diagram of a customized sleep learning system for infants and toddlers according to the present invention, FIG. 3 is an embodiment of the block diagram of a customized sleep learning system for infants and toddlers according to the present invention, FIG. 4 is a diagram illustrating the function of a sleep state detection unit, FIG. 5 is a diagram illustrating the function of a customized learning content provision unit, FIG. 6 is a diagram illustrating the function of a parent interface, and FIG. 7 is a diagram illustrating an example of sleep education according to the present invention.

[0022] The sleep learning system (1) customized for infants and toddlers according to the present invention detects the sleep state of an infant and toddler in real time and improves sleep patterns by analyzing the detected data and providing customized learning content. The sleep state detection unit (10) is a key component for detecting the sleep state of an infant and toddler in real time and includes a heart rate sensor (100) that measures the infant and toddler's heart rate in real time and provides data to determine whether the infant and toddler is in a sleep state or awake state, a body temperature sensor (110) that detects changes in the infant and toddler's body temperature to monitor fever or body temperature stability during sleep, and a motion sensor (120) that analyzes movement data during sleep to detect signals indicating tossing and turning or the possibility of waking up during sleep. The sleep state detection unit (10) integrates the data from the above sensors to determine the sleep state of the infant and toddler in real time and transmits this data to the data processing unit (20).

[0023] As an example, when an infant enters a sleep state, each sensor of the sleep state detection unit (10) collects data in the following manner. The heart rate sensor (100) measures the infant's heart rate at least twice per second and calculates the average heart rate to determine the sleep stage (light sleep, deep sleep, etc.). For example, if the heart rate is stable at 70 BPM or less, it is determined to be in a deep sleep state. The body temperature sensor (110) detects the infant's skin temperature in seconds and checks whether the body temperature is maintained within a certain range (36.5~37.5℃) during sleep. If the body temperature rises or falls, the system records the data and sends a notification to the parent interface (40). The motion sensor (120) analyzes the sleep state by recording the frequency of the infant tossing and turning or moving their body up to 10 times per second. If there is almost no movement, it is determined to be a stable sleep state, and if continuous movement is detected, the quality of sleep is evaluated as low.

[0024] By synthesizing the data from the sleep state detection unit (10), the following information can be derived: Average heart rate: 75 BPM (recorded over 7 hours). Average body temperature: 36.8℃ (±0.2℃ fluctuation). Number of tossing and turning: 3 times per hour. The above data is transmitted to the data processing unit (20) so that the sleep pattern analysis module (200) can comprehensively evaluate the sleep state. As another example, if an infant or toddler exhibits an abnormal physical condition during sleep, the sleep state detection unit (10) immediately sends a warning to the infant / toddler customized sleep learning system (1). For example, if the heart rate rises above 100 BPM and the body temperature rises to 38℃, or if irregular movement is detected by the motion sensor (120), the following notification is sent through the parent interface (40): "The infant / toddler's heart rate has risen. Check their current condition." "The body temperature has exceeded the normal range. Take appropriate action."

[0025] The data processing unit (20) is a core component that collects and analyzes data transmitted from the sleep state detection unit (10) to derive the sleep pattern of the infant. The sleep pattern analysis module (200) within the data processing unit (20) organizes the data provided by the sleep state detection unit (10) in time units and analyzes the infant's heart rate, body temperature, and movement patterns to derive the sleep stage (deep sleep, light sleep, REM sleep, etc.). It calculates indicators that evaluate the quality of sleep, such as the frequency of awakening, the duration of sleep, and the number of times the infant tosses and turns. The learning content optimization module (210) recommends learning content optimized for the infant's current sleep state based on the results analyzed by the sleep pattern analysis module (200). For example, it is set to provide white noise if there is a need to induce deep sleep, or it is decided to provide story content if emotional stability is needed.

[0026] The customized learning content provision unit (30) provides customized learning content based on the analysis results of the data processing unit (20). The white noise provision module (300) within the customized learning content provision unit (30) plays white noise of a suitable frequency according to the sleep state of the infant. The story provision module (310) provides emotionally beneficial story content so that the infant can feel a sense of stability. The lullaby provision module (320) selects and plays a lullaby suitable for the age and sleep state of the infant. Each content can automatically adjust the playback time and volume by monitoring the infant's reaction in real time.

[0027] As one example, if an infant is in a light sleep state or if ambient noise (e.g., 50 dB or higher) is detected, the learning content optimization module (210) of the data processing unit (20) activates the white noise provision module (300). The white noise provision module (300) plays soft white noise of 30 dB to block external noise and stabilize the infant's brainwaves to induce deep sleep. During playback, the infant's heart rate and movement data are monitored in real time, and the volume of the white noise is gradually reduced when the infant transitions to a stable state. As another example, before the infant enters sleep, the story provision module (310) is activated according to the analysis results of the data processing unit (20). Through the parent interface (40), storybook content is selected, or a sleep-inducing story such as "The Little Lamb's Dream" is automatically played. The story content is played for about 5 to 10 minutes, and playback ends when the infant's movement decreases and the infant enters a stable state. As another example, if the infant is detected to be in a light sleep state or if the body temperature and heart rate are unstable, the lullaby providing module (320) is activated. The module plays a classic lullaby (e.g., Brahms' Lullaby) at a low volume of 20 dB and adjusts the playback length according to the infant's condition. If the infant's movement data decreases rapidly and the heart rate stabilizes during playback, playback is terminated.

[0028] The parent interface (40) provides an interface that allows parents to check the sleep status of the infant in real time and adjust content provision settings. The status monitoring module (400) visualizes data collected from the sleep status detection unit (10) and the data processing unit (20) so that parents can grasp the sleep status of the infant at a glance. The setting adjustment module (410) can adjust content playback time, volume, content type, etc., and also includes a function to schedule content at a time desired by the parents.

[0029] As one example, the status monitoring module (400) visually displays data collected from the sleep state detection unit (10) and the data processing unit (20) to the parents in real time. Key status information of the infant is displayed as follows: Heart rate: 75 BPM (current stable state). Body temperature: 36.8℃ (normal range). Sleep stage: deep sleep stage. Movement data: number of movements 2 times per hour (normal movement pattern). This information is provided to the parents through an application (3) on a smart device (2) owned by the parents. During this provision process, graphs and icons are used to visualize the data so that it can be checked at a glance. For example, changes in heart rate are displayed as a real-time graph. Body temperature is displayed by distinguishing between within and outside the normal range using colors (e.g., green = normal, red = abnormal). As another example, through the setting adjustment module (410), parents can adjust the method of providing content according to the infant's sleep state. The items that parents can set are as follows. White noise volume adjustment allows the white noise volume to be adjusted from 20dB to 30dB to block external noise when the infant is in a light sleep state. Content playback time setting extends the lullaby playback time from 10 minutes to 20 minutes to help the infant fall asleep stably. Story content selection selects "The Story of a Little Star Under the Moonlight" from the fairy tales to induce emotional stability in the infant. As an example, all settings can be operated remotely via an application (3) on a smart device (2) owned by the parent.

[0030] The parent interface (40) sends a warning notification when an abnormality is detected in the infant's condition. For example, if the heart rate rises above 100 BPM or the body temperature is detected to be above 38℃, it immediately sends a notification stating, "Infant condition warning: Heart rate / body temperature is abnormal." If the motion sensor (120) detects continuous movement, it sends a notification stating, "There is a possibility that the infant is waking up. Please check." The notification is provided in real-time to the parent's smart device (2) in the form of a push message.

[0031] The data analysis learning module (500) within the artificial intelligence learning module (50) continuously learns sleep state detection and content provision data to optimize the method of providing content according to changes in the sleep state of infants and toddlers. The content improvement module (510) performs the role of further improving the sleep quality of infants and toddlers by adding new content or improving existing content based on the learned data.

[0032] As an example, when an infant is sleeping, the sleep state detection unit (10) collects heart rate, body temperature, and movement data in real time. For example, the heart rate sensor (100) checks whether the infant's heart rate is between 60 and 90 BPM, and the body temperature sensor (110) measures whether the body temperature is maintained between 36.5 and 37.5℃. The movement sensor (120) detects when the infant tosses and turns and records the data. The sleep pattern analysis module (200) determines whether the infant is currently in a deep sleep stage, a light sleep stage, or an awake state based on the detected data. If the analysis result indicates that the infant is in a light sleep stage, the learning content optimization module (210) is set to provide white noise. Based on the analysis result of the data processing unit (20), the white noise provision module (300) plays soft white noise of 20 to 30 dB and checks whether movement decreases and the infant enters a deep sleep stage. Parents can check the infant's current heart rate, body temperature, and movement data in real time through the status monitoring module (400), and can extend the content playback time or add specific content through the setting adjustment module (410). The artificial intelligence learning module (50) continuously learns the infant's sleep pattern data and evaluates whether providing content is effective for improving sleep. For example, if it is confirmed that a specific lullaby is effective for inducing deep sleep, the content improvement module (510) sets that lullaby as default content.

[0033] A sleep pattern analysis module (200), which is a component of a data processing unit (20) according to one embodiment of the present invention, collects and stores data provided by a sleep state detection unit (10) in hourly, weekly, and monthly units. Regarding hourly data, it detects changes in sleep state (deep sleep, light sleep, wakefulness, etc.) over a day, and regarding weekly data, it analyzes the average sleep time, wakefulness frequency, and movement patterns over a week. Regarding monthly data, it comprehensively analyzes sleep patterns over a month to evaluate long-term sleep changes. A learning content optimization module (210), which is a component of the data processing unit (20), scores the sleep state of an infant based on the analyzed data (e.g., 0 to 100 points) or provides it to a parent interface (40) in the form of graphs and charts. Regarding sleep time, it calculates the average daily sleep time (e.g., 7 hours and 20 minutes) and the average weekly or monthly sleep time, and regarding wakefulness frequency, it measures the number of times the infant woke up during sleep and provides an average value (e.g., an average of 3 times per week). In relation to movement patterns, sleep quality is evaluated based on the number of times or intensity of movement during sleep.

[0034] In a specific embodiment, the sleep state detection unit (10) detects the heart rate, body temperature, and movement data of an infant in real time and transmits them to the data processing unit (20). Regarding the data collection process, if the heart rate is stable at 60 to 70 BPM, it is determined to be a deep sleep state, and if the body temperature is maintained within the range of 36.5 to 37.0℃, it is evaluated as a normal sleep state. If movement is detected 2 to 3 times per hour by the movement sensor (120), it is determined to be a good sleep state. The sleep pattern analysis module (200) generates the following information based on data over 24 hours: Deep sleep: 3 hours 40 minutes. Light sleep: 2 hours 20 minutes. Awake time: 20 minutes. The above data is provided as a real-time graph on the parent interface (40).

[0035] As an example, weekly data derives patterns by collecting 7 days of sleep data. For instance, the average sleep time over 7 days is 7 hours and 15 minutes. The frequency of awakenings is 3 times per week. The movement pattern is an average of 2 tossing and turning per hour. The analysis results are provided as follows. For instance, the weekly sleep quality score is calculated as 85 points (out of 100). The change graph visualizes changes in awakening frequency and sleep time, allowing parents to grasp the sleep status over the course of a week at a glance.

[0036] Monthly data serves as information for evaluating long-term sleep status and comprehensively analyzes 30 days of data. The collected data shows a monthly average sleep time of 7 hours and 10 minutes, a monthly average frequency of awakenings of 12 times, and a monthly average number of movements of 2.5 times / hour. The analysis results are provided as follows: regarding long-term sleep patterns, the monthly average sleep time decreased by 15 minutes compared to the previous month, and the improvement score indicates a 5% improvement in sleep quality compared to the previous month.

[0037] The parent interface (40) according to the present invention recommends improved sleep content through an artificial intelligence learning module (50) along with monthly data. As one example, the quantified indicators provided by the sleep state detection unit (10) and the data processing unit (20) are utilized as follows: Sleep quality score: evaluated from 0 to 100 points. 80 points or more: good sleep state. 60 to 79 points: state requiring attention. 59 points or less: state requiring improvement. If the monthly sleep quality score is low, the parent selects to extend the playback time of the lullaby providing module (320). If the frequency of awakening is high, the frequency of the white noise providing module (300) is adjusted to induce deep sleep.

[0038] The customized learning content providing unit (30) according to the present invention is composed of a white noise providing module (300), a story providing module (310), and a lullaby providing module (320), and operates in the following manner. The content playback time is extended or shortened depending on the sleep state of the infant. For example, when the infant is in a light sleep state, the content is played for a longer period to induce stable sleep. The content volume is adjusted by analyzing the ambient noise level and the infant's movement data. If a specific content is effective for inducing sleep, the content is played repeatedly. The infant's heart rate, body temperature, and movement data are monitored in real time to evaluate the response to the content. The collected data is transmitted to the data processing unit (20) and the artificial intelligence learning module (50) to learn and improve effective content provision methods.

[0039] In a specific embodiment, if the sleep state detection unit (10) detects that the infant is in a light sleep state (e.g., frequent movement and high heart rate), the white noise providing module (300) is set to play white noise for 15 minutes. After 15 minutes, the infant's heart rate and movement data are re-evaluated to check if the infant has transitioned to a deep sleep state. If the sleep state has not improved, the content playback time is extended by an additional 10 minutes. If the infant is in a deep sleep state (stable heart rate, no movement), the story providing module (310) plays the story content at a low volume (20 dB). If ambient noise (e.g., 40 dB or higher) is detected, the story volume is automatically adjusted to 30 dB to maximize the noise blocking effect. If the sleep state becomes unstable, the content volume is lowered again to stabilize the infant. As an example, the lullaby providing module (320) plays "Brahms' Lullaby" and the sleep state detection unit (10) evaluates whether the infant has transitioned to a stable state. If the infant's heart rate and movement do not stabilize during the first repeated playback, the lullaby is set to be played twice. If the infant does not stabilize even after repeated playback, the content type is switched to story content. The customized learning content providing unit (30) collects the infant's reaction data in real time during content playback. For example, when playing "Brahms' Lullaby," the heart rate stabilization time is recorded as an average of 10 minutes. The data processing unit (20) analyzes the data to confirm that the lullaby is effective content. The artificial intelligence learning module (50) learns this data to set the default playback time of the lullaby providing module (320) to 10 minutes and suggests an effective volume level. Based on the infant's sleep state and past data, the customized learning content providing unit (30) implements the following optimized content provision method. It is set to prefer story content during the day. At night, it prioritizes white noise to block out external noise.If you tend to have short sleep durations, set lullabies as the default content to induce sleep.

[0040] In one embodiment of the present invention, another parent interface (40) is composed of a status monitoring module (400) and a settings adjustment module (410), and focuses on visually providing sleep logs and analysis data. The status monitoring module (400) visually displays sleep patterns and status based on data provided by the sleep status detection unit (10) and the data processing unit (20). It intuitively represents data using graphs, charts, and icons. The settings adjustment module (410) supports parents in adjusting the content delivery method and settings (e.g., content playback time, volume, type) based on the visualized data.

[0041] In relation to an embodiment for automatic recording and visualization of a sleep diary, the data collected by the sleep state detection unit (10) is organized by the data processing unit (20) and provided to the parent interface (40). Sleep time, number of awakenings, frequency of movement, changes in body temperature, heart rate data, etc., are recorded, automatically recorded daily, summarized on a weekly and monthly basis, and visualized data is provided. For example, daily sleep data displays sleep time and the number of awakenings as a bar graph. Regarding weekly and monthly sleep data, the weekly average sleep time and the number of awakenings are represented as a line graph.

[0042] The parent interface (40) performs an in-depth analysis of sleep state data and provides it in the following forms. Regarding the analysis of sleep stages, it displays the ratios of deep sleep, light sleep, and wakefulness in a pie chart, and regarding the analysis of movement data, it provides the number of movements per hour in the form of a histogram. Accordingly, it provides a summary of changes in the infant's sleep pattern, such as, "The sleep pattern this week is stable. The average sleep time has increased by 15 minutes compared to last week." "The frequency of awakenings has decreased, and the quality of sleep has improved." The parent interface (40) provides notifications to parents based on the visualized data. For example, it provides notifications such as, "The infant's sleep time is shorter than average. We recommend playing lullaby content." "Deep sleep time has decreased. Please consider playing white noise content." In addition, based on the data analyzed by the artificial intelligence learning module (50), it suggests the optimal method for providing content. For example, "Recommendation to adjust story content playback time: 10 minutes → 15 minutes."

[0043] In the example of diagnosing and improving sleep problems, if parents check the weekly sleep log data and find that the infant's deep sleep time is shorter than average, the parents set the playback time of the lullaby providing module (320) to be extended from 10 minutes to 20 minutes and lower the volume through the setting adjustment module (410). Subsequently, as a result of analyzing the sleep data, the deep sleep time increases by 30%, and the quality of sleep improves. In the example of monitoring changes in sleep patterns, the parent interface (40) can summarize the changes in sleep patterns compared to the previous month as follows: "Deep sleep time increased by 10%." "The frequency of awakenings decreased from 12 times per month to 8 times." Through this data, parents can confirm that the infant's sleep environment is improving.

[0044] According to one embodiment of the present invention, the data analysis learning module (500) within the artificial intelligence learning module (50) learns data collected from the sleep state detection unit (10) and the data processing unit (20) to analyze changes in sleep patterns on an hourly, weekly, and monthly basis. It evaluates whether there is improvement based on the sleep state of the infant (heart rate, body temperature, movement data) and optimizes the method of providing customized learning content based on this. For example, it can learn that the deep sleep time of the infant increases when white noise is played. The content improvement module (510) evaluates the effectiveness of the provided content to identify highly effective content and improve inefficient content. It continuously improves the method of providing content by adjusting the playback time, volume, type, etc. of the content. For example, it can analyze that lowering the lullaby volume from 25dB to 20dB is effective and can improve it.

[0045] In relation to an example of sleep pattern analysis through data learning, the data collection and learning process involves collecting heart rate, body temperature, and movement data in real time from a sleep state detection unit (10) and organizing them in time units through a data processing unit (20). The data analysis learning module (500) learns the collected data to derive changes in sleep patterns. For example, the analysis results may be derived from the data learning results over the past 7 days, such as confirming a pattern where sleep becomes unstable between 10:00 and 11:00 every night, such as when white noise content is played during the light sleep stage of an infant, the time taken to transition to deep sleep is shortened by an average of 15 minutes.

[0046] The data analysis learning module (500) activates the white noise provision module (300) and sets it to provide customized content during the corresponding time period. As an example, regarding the evaluation of content effectiveness, the content improvement module (510) compares the sleep-inducing effects of white noise, lullabies, and story content. For example, it is possible to derive effects such as a 40% increase in deep sleep time when playing white noise, a 25% increase when playing lullabies, and minimal effect when playing story content. To improve these contents, the volume and melody of the lullaby can be adjusted during playback, or the story content can be improved by adding background music and shortening the length (10 minutes → 5 minutes). As an example, regarding the improvement effects, it is confirmed that the improved lullaby increases deep sleep time by 35%, and that the story content increases emotional stability.

[0047] The data analysis learning module (500) learns data on a monthly basis to evaluate long-term changes in sleep patterns. For example, it confirms that infants tend to have lower body temperatures and reduced deep sleep time during a specific season (winter). The content improvement module (510) develops content that combines warm-feeling music and white noise to improve sleep conditions during the winter. As an example, the playback time of the content is extended from the existing 20 minutes to 30 minutes. As an example of the results, it can be confirmed that the average deep sleep time of infants increases by 30 minutes after the new content is provided.

[0048] FIG. 8 is a flowchart illustrating a customized sleep learning method for infants and toddlers according to the present invention, FIG. 9 is a diagram illustrating the additional implementation of artificial intelligence functions in the customized sleep learning method for infants and toddlers according to the present invention, and FIG. 10 is a diagram illustrating an application in which the present invention is implemented.

[0049] In the sleep state detection step (S100) of the customized sleep learning method for infants and toddlers according to the present invention, biological data of the infant and toddler is detected and collected in real time through the sleep state detection unit (10). The heart rate sensor (100) detects the heart rate of the infant and toddler in real time and provides data for determining the sleep stage (deep sleep, light sleep, wakefulness). The body temperature sensor (110) detects changes in body temperature to check whether a stable body temperature is maintained during sleep. The motion sensor (120) detects tossing and turning and changes in posture during sleep to evaluate the quality and stability of sleep.

[0050] Next, in the data processing and analysis step (S200), the data collected in the sleep state detection step (S100) is transmitted to the data processing unit (20) for analysis. The sleep pattern analysis module (200) analyzes the sleep duration, wakefulness frequency, body temperature fluctuations, and movement patterns on an hourly basis to quantify the sleep state of the infant. The learning content optimization module (210) derives customized learning content based on the analyzed data and determines the content type (white noise, story, lullaby) and delivery method (playback time, volume, number of repetitions).

[0051] The customized learning content provision step (S300) provides the derived content to the infant through the customized learning content provision unit (30). The white noise provision module (300) plays white noise of a specific frequency to block external noise and induce deep sleep. As an example, regarding the specific frequency of white noise, for infants, a low-frequency band of 1,000 Hz or lower is mainly effective. This frequency range is similar to sounds inside the womb and provides a sense of stability to the infant. For example, 125 Hz to 250 Hz is a soft sound that provides psychological stability to the infant. 500 Hz to 1,000 Hz is suitable for blocking ambient noise and inducing sleep in infants.

[0052] The story providing module (310) provides fairy tale stories or content with a soft voice for the emotional stability of infants and toddlers. The lullaby providing module (320) plays a lullaby with a suitable melody to promote sleep in infants and toddlers. In response to this, the infant's reaction data is analyzed in real time, and the playback time, volume, and repetition count of the content are automatically adjusted.

[0053] Next, in the monitoring and setting adjustment step (S400), the content provided through the parent interface (40) and the sleep status data of the infant can be visualized in real time, and settings can be adjusted. The status monitoring module (400) provides heart rate, body temperature, movement data, and sleep status (deep sleep, light sleep, wakefulness) in the form of graphs and charts. The setting adjustment module (410) supports parents in adjusting the content playback time, volume, and repetition count, or changing the content type.

[0054] Finally, in the learning content improvement step through feedback (S500), the data analysis learning module (500) learns the detected data and the results of content provision to analyze whether there is a change or improvement in the sleep pattern. For example, it learns that white noise content is effective in transitioning from a light sleep state to deep sleep. The content improvement module (510) evaluates the effectiveness of the provided content and continuously improves the content type, playback time, volume, etc. For example, it can be "improving the sleep promotion effect by 20% through the adjustment of the lullaby melody and volume."

[0055] In relation to a specific embodiment, during the process of providing customized content and automatic adjustment, the initial state is detected as follows: Heart rate sensor (100): 80 BPM → light sleep state; Body temperature sensor (110): 37.0℃ → stable state; Motion sensor (120): 5 movements in 10 minutes → unstable sleep state. The white noise providing module (300) plays white noise at 25 dB, and the lullaby providing module (320) provides a lullaby with the number of repeated plays set to 2. When the infant's heart rate stabilizes at 70 BPM, the number of lullaby repetitions is stopped, and the white noise volume is gradually lowered. As an example, if the analysis of data learning results over the past 7 days indicates that white noise content is more effective than lullabies in inducing sleep, the playback time of the white noise is extended from the existing 10 minutes to 15 minutes in relation to content improvement. The volume of the lullaby is lowered from 25 dB to 20 dB. As a concrete result, it can be confirmed that the average deep sleep time increased by 30 minutes after providing improved content.

[0056] In the present invention, the artificial intelligence learning module (50) learns data collected from the sleep state detection unit (10) and the data processing unit (20) in the improved data processing and analysis learning step (S210) to comprehensively analyze the sleep time, wake frequency, body temperature change, and movement pattern of the infant. Next, in the improved optimized learning content automatic recommendation step (S310), based on the analysis results, it evaluates the changes in the infant's sleep habits and the quality of the sleep state, and automatically recommends optimized content according to the changes in the sleep pattern. The content improvement module (510) within the artificial intelligence learning module (50) evaluates the effectiveness of the provided learning content in the improved learning content effectiveness evaluation and improvement step (S510), continuously utilizes content with high effectiveness, and improves inefficient content. By adjusting the content type, playback time, volume, etc., it realizes the provision of content optimized for the infant's sleep state and habits.

[0057] In relation to the example of data learning and analysis of changes in sleep habits, heart rate: average 75 BPM → derivation of deep sleep state. Body temperature: maintained at 36.8℃ → evaluation of stable sleep environment. Movement: 2 movements per hour → good sleep pattern. It can be detected, and the analysis results confirm that when white noise is played to infants in a light sleep state, the time to transition to deep sleep is shortened by an average of 10 minutes. By analyzing the tendency for sleep onset time to be delayed every Monday night, lullaby content is recommended preferentially during that time. The data analysis learning module (500) automatically recommends white noise content (playback time 15 minutes, volume 25dB) during the light sleep stage. Lullaby content is provided preferentially during the time period when there is a tendency for sleep time to be delayed. In relation to evaluating and improving the effectiveness of the content, after providing the content, the increase in deep sleep time, decrease in the frequency of awakenings, and the stabilization of movement patterns are analyzed. After playing white noise, deep sleep time increases by an average of 20 minutes. Regarding content improvement, the content improvement module (510) adjusts the types and settings of content with low effectiveness, for example, by modifying the melody of lullaby content to increase the sleep-promoting effect by 15%, or by shortening the length of story content from the existing 10 minutes to 7 minutes to improve the effect. As a result of the improvement, it can be confirmed that the improved lullaby has the effect of increasing deep sleep time by an additional 10 minutes.

[0058] In relation to an example of providing optimized content based on changes in sleep habits, the data analysis learning module (500) learns the monthly data of infants and toddlers to derive changes in sleep habits. For example, it analyzes the tendency for body temperature to rise and sleep quality to deteriorate during a specific season (summer), and the content improvement module (510) recommends white noise combined with natural sounds to improve sleep quality during the summer, and extends the playback time from the existing 10 minutes to 20 minutes. As a result of the experiment, it can be confirmed that after providing the optimized content, the average deep sleep time increases by 25 minutes and the frequency of awakening decreases by 30%.

[0059] The smart device (2) implementing a customized sleep learning method for infants and toddlers according to an embodiment of the present invention may include not only general PCs such as general desktops or laptops, but also mobile terminals such as smartphones, tablet PCs, PDAs (Personal Digital Assistants), and mobile communication terminals, and should be interpreted as any device capable of computing. The operating system of the smart device (2) may be an operating system such as Windows or Macintosh installed on general PCs such as desktops and laptops, or a mobile-specific operating system such as iOS or Android installed on mobile terminals such as smartphones and tablet PCs.

[0060] A customized sleep learning program for implementing a customized sleep learning method for infants and toddlers according to an embodiment of the present invention may be disclosed, and such a customized sleep learning program may be implemented as an application (3) and may be stored on a computer-readable recording medium. In order for a computer to read a clothing manufacturing program stored on a recording medium and execute the embodiments implemented as a program, the customized sleep learning program may include code coded in a computer language such as C, C++, JAVA, or machine language that can be read by a computer processor (CPU). Such code may include functional code related to functions that define the aforementioned functions, and may also include control code related to execution procedures necessary for the computer processor to execute the aforementioned functions according to a predetermined procedure.

[0061] Furthermore, such code may further include memory reference-related code regarding where (address) in the computer's internal or external memory additional information or media required for the computer's processor to execute the aforementioned functions should be referenced. Additionally, if the computer's processor requires communication with any other remote computer or server, etc., to execute the aforementioned functions, the code may further include communication-related code regarding how the computer's processor should communicate with any other remote computer or server, etc., using the computer's communication module (e.g., wired and / or wireless communication module), and what information or media should be transmitted or received during communication.

[0062] Furthermore, the customized sleep learning program for implementing the embodiments described above, and the related code and code segments, etc., may be easily inferred or modified by programmers skilled in the art to which the present invention belongs, taking into account the system environment of a computer that reads the recording medium and executes the program. In addition, a computer-readable recording medium storing the customized sleep learning program described above may be distributed across networked computer systems, so that computer-readable code can be stored and executed in a distributed manner. In this case, one or more of the multiple distributed computers may execute some of the functions presented above and transmit the results to one or more of the other distributed computers, and the computer that receives the results may also execute some of the functions presented above and provide the results to other distributed computers.

[0063] Overall, this invention effectively resolves sleep problems in infants and toddlers and contributes to their emotional stability and the formation of healthy sleep patterns by providing customized content. Continuous improvement is possible through an AI learning module, and the burden of childcare is alleviated for parents by supporting real-time monitoring and management. This is an innovative system that has a positive impact on the growth and development of infants and toddlers and can contribute to reducing social costs in the long term.

[0064] The foregoing description is merely an illustrative explanation of the technical concept of the present invention, and those skilled in the art to which the present invention pertains will be able to make various modifications and variations within the scope of the essential characteristics of the present invention. Accordingly, the embodiments disclosed in the present invention are intended to explain, not limit, the technical concept of the present invention, and the scope of the technical concept of the present invention is not limited by these embodiments. The scope of protection of the present invention shall be interpreted by the claims below, and all technical concepts within an equivalent scope shall be interpreted as being included within the scope of rights of the present invention. Explanation of the symbols

[0065] 1: Infant-Customized Sleep Learning System 2: Smart device 3: Application 10: Sleep state detection unit 100: Heart rate sensor 110: Body temperature sensor 120: Motion sensor 20: Data processing unit 200: Sleep Pattern Analysis Module 210: Learning Content Optimization Module 30: Personalized Learning Content Provision Department 300: White Noise Provider Module 310: Story Provision Module 320: Lullaby Provider Module 40: Parent Interface 400: Status Monitoring Module 410: Configuration Adjustment Module 50: Artificial Intelligence Learning Module 500: Data Analysis Learning Module 510: Content Improvement Module

Claims

Claim 1 A sleep learning system for infants and toddlers that detects the sleep state of an infant and toddler and provides customized learning content, wherein the sleep learning system for infants and toddlers comprises: a sleep state detection unit including a heart rate sensor, a body temperature sensor, and a motion sensor for detecting the sleep state of an infant and toddler; a data processing unit including a sleep pattern analysis module and a learning content optimization module that collect and analyze data detected by the sleep state detection unit to derive a sleep pattern; a customized learning content providing unit that provides learning content including a customized white noise providing module, a story providing module, and a lullaby providing module according to the analysis results of the data processing unit; and a parent interface that allows parents to check the sleep state of an infant and toddler in real time and adjust settings through a state monitoring module and a setting adjustment module. Claim 2 A customized sleep learning system for infants and toddlers that supports improving sleep patterns by detecting the sleep state of the infant in real time and providing customized learning content comprises: a heart rate sensor that detects the infant's heart rate data in real time; a body temperature sensor that detects changes in the infant's body temperature; and a motion sensor that detects the infant's movement and changes in posture during sleep; a sleep state detection unit that continuously monitors the sleep state based on the detected data; a sleep pattern analysis module that analyzes data collected from the sleep state detection unit to derive the sleep state and sleep pattern; and a learning content optimization module that selects and provides learning content optimized for the infant's sleep state based on the sleep pattern analysis results; a customized learning content provision unit that includes a white noise provision module that provides white noise according to the sleep state derived from the data processing unit; a story provision module that provides story content for sleep induction and emotional stability; and a lullaby provision module that provides a lullaby to promote sleep; and a parent interface that supports parents in checking the infant's sleep state and sleep pattern analysis data in real time through a state monitoring module and adjusting the playback settings, volume control, and playback time settings of the sleep learning content through a setting adjustment module. A sleep learning system tailored for infants and toddlers, characterized by including Claim 3 A sleep learning system tailored for infants and toddlers according to paragraph 2, wherein the data processing unit collects data from the sleep state detection unit in hourly, weekly, and monthly units, and comprehensively analyzes sleep duration, wakefulness frequency, and movement patterns during sleep to provide the sleep state of the infant or toddler as a quantified indicator. Claim 4 In paragraph 2, the customized learning content providing unit automatically adjusts the playback time, volume, and repetition count of the content according to the sleep state of the infant, and collects response data of the infant to optimize the method of providing the content, thereby creating a customized sleep learning system for infants. Claim 5 A sleep learning system tailored for infants and toddlers, characterized in that, in paragraph 2, the parent interface visualizes and provides the infant's sleep diary and sleep state analysis data in a graphical form, thereby enabling parents to grasp changes in the infant's sleep pattern at a glance. Claim 6 A sleep learning system tailored for infants and toddlers according to claim 2, wherein the artificial intelligence learning module continuously learns data collected from the sleep state detection unit and the data processing unit to analyze changes and improvements in sleep patterns and optimizes the method of providing customized learning content accordingly; and a content improvement module that improves sleep content; characterized in that the artificial intelligence learning module comprises: a data analysis learning module that analyzes changes and improvements in sleep patterns and optimizes the method of providing customized learning content accordingly; and a content improvement module that improves sleep content. Claim 7 A sleep learning method for infants and toddlers that improves sleep patterns by detecting and analyzing the sleep state of the infant and toddler and providing customized learning content, comprising: a sleep state detection step for detecting the sleep state of the infant and toddler by detecting heart rate data through a heart rate sensor, detecting body temperature data through a body temperature sensor, and detecting movement and posture changes during sleep through a motion sensor, and collecting data detected by a sleep state detection unit in real time; a data processing and analysis step for transmitting the data collected in the sleep state detection step to a data processing unit, quantifying the sleep state of the infant and toddler by analyzing data including hourly sleep duration, wakefulness frequency, body temperature fluctuations, and movement patterns through a sleep pattern analysis module, and deriving customized learning content according to the analyzed sleep state and sleep pattern using a learning content optimization module; wherein, according to the results derived in the data processing and analysis step, white noise to induce sleep in the infant and toddler is provided through a white noise provision module, story content for the emotional stability of the infant and toddler is provided through a story provision module, and lullaby content to promote sleep is provided through a lullaby provision module, provided according to the infant and toddler's response and sleep state A customized learning content provision step that provides content by automatically adjusting the volume, playback time, and repetition count of the content; a monitoring and setting adjustment step through the parent interface that provides the sleep learning content and the sleep state data of the infant provided in the content provision step in a real-time visualized form through the status monitoring module of the parent interface, and allows the parent to adjust settings such as the content playback time, volume, and type as needed through the setting adjustment module;A sleep learning method tailored for infants and toddlers, characterized by including: a learning content improvement step through feedback, wherein the data obtained from the sleep state detection step and the data processing and analysis step is continuously learned using the data analysis learning module of the artificial intelligence learning module, and based on the learned results, customized content optimized for the future sleep state and pattern of the infant and toddler is automatically improved and provided through a content improvement module. Claim 8 A sleep learning method for infants and toddlers customized according to claim 7, wherein the artificial intelligence learning module comprehensively analyzes the sleep duration, wakefulness frequency, body temperature changes, and movement patterns of an infant and toddler based on data collected from the sleep state detection unit and the data processing unit in the data processing and analysis step, learns the results analyzed in the customized learning content provision step through the data analysis learning module to automatically recommend learning content optimized according to changes in the sleep habits of the infant and toddler, and evaluates and improves the effectiveness of the provided learning content through the content improvement module in the learning content improvement step.

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